Overview

Dataset statistics

Number of variables15
Number of observations11813
Missing cells0
Missing cells (%)0.0%
Duplicate rows26
Duplicate rows (%)0.2%
Total size in memory1.4 MiB
Average record size in memory120.0 B

Variable types

NUM13
BOOL1
CAT1

Warnings

Dataset has 26 (0.2%) duplicate rows Duplicates
Class has 386 (3.3%) zeros Zeros

Reproduction

Analysis started2022-03-20 19:46:55.224716
Analysis finished2022-03-20 19:47:14.634228
Duration19.41 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Popularity
Real number (ℝ≥0)

Distinct97
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.10065182
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:14.713837image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16
Q132
median42
Q354
95-th percentile72
Maximum98
Range97
Interquartile range (IQR)22

Descriptive statistics

Standard deviation16.56849968
Coefficient of variation (CV)0.3844141324
Kurtosis-0.1209540338
Mean43.10065182
Median Absolute Deviation (MAD)11
Skewness0.08463601659
Sum509148
Variance274.5151816
MonotocityNot monotonic
2022-03-20T19:47:14.821835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
423242.7%
 
413172.7%
 
433092.6%
 
343092.6%
 
403032.6%
 
373012.5%
 
442952.5%
 
462902.5%
 
362792.4%
 
382782.4%
 
Other values (87)880874.6%
 
ValueCountFrequency (%) 
1390.3%
 
2250.2%
 
3310.3%
 
4280.2%
 
5330.3%
 
ValueCountFrequency (%) 
981< 0.1%
 
971< 0.1%
 
955< 0.1%
 
942< 0.1%
 
932< 0.1%
 

danceability
Real number (ℝ≥0)

Distinct873
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5249440024
Minimum0.0644
Maximum0.989
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:14.924365image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0644
5-th percentile0.245
Q10.413
median0.527
Q30.638
95-th percentile0.8004
Maximum0.989
Range0.9246
Interquartile range (IQR)0.225

Descriptive statistics

Standard deviation0.1660125113
Coefficient of variation (CV)0.3162480389
Kurtosis-0.3135549116
Mean0.5249440024
Median Absolute Deviation (MAD)0.112
Skewness-0.03762915605
Sum6201.1635
Variance0.0275601539
MonotocityNot monotonic
2022-03-20T19:47:15.026592image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.527480.4%
 
0.533430.4%
 
0.545410.3%
 
0.489410.3%
 
0.601400.3%
 
0.529390.3%
 
0.556380.3%
 
0.508380.3%
 
0.467370.3%
 
0.469370.3%
 
Other values (863)1141196.6%
 
ValueCountFrequency (%) 
0.06441< 0.1%
 
0.06461< 0.1%
 
0.0651< 0.1%
 
0.06971< 0.1%
 
0.07261< 0.1%
 
ValueCountFrequency (%) 
0.9891< 0.1%
 
0.9822< 0.1%
 
0.983< 0.1%
 
0.9791< 0.1%
 
0.9731< 0.1%
 

energy
Real number (ℝ≥0)

Distinct1147
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6703048701
Minimum2.03e-05
Maximum1
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:15.129631image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2.03e-05
5-th percentile0.186
Q10.513
median0.716
Q30.875
95-th percentile0.971
Maximum1
Range0.9999797
Interquartile range (IQR)0.362

Descriptive statistics

Standard deviation0.2423240011
Coefficient of variation (CV)0.3615131143
Kurtosis-0.3029331728
Mean0.6703048701
Median Absolute Deviation (MAD)0.176
Skewness-0.7191973851
Sum7918.31143
Variance0.05872092152
MonotocityNot monotonic
2022-03-20T19:47:15.236580image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.931430.4%
 
0.948410.3%
 
0.932400.3%
 
0.913390.3%
 
0.971390.3%
 
0.964380.3%
 
0.872380.3%
 
0.963360.3%
 
0.914360.3%
 
0.974350.3%
 
Other values (1137)1142896.7%
 
ValueCountFrequency (%) 
2.03e-051< 0.1%
 
0.001241< 0.1%
 
0.00171< 0.1%
 
0.003011< 0.1%
 
0.003951< 0.1%
 
ValueCountFrequency (%) 
11< 0.1%
 
0.9993< 0.1%
 
0.9984< 0.1%
 
0.99780.1%
 
0.996100.1%
 

key
Real number (ℝ≥0)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.97257259
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:15.322237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.167348359
Coefficient of variation (CV)0.5303155903
Kurtosis-1.199195582
Mean5.97257259
Median Absolute Deviation (MAD)3
Skewness-0.06481665455
Sum70554
Variance10.03209562
MonotocityNot monotonic
2022-03-20T19:47:15.392081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
7162613.8%
 
2152612.9%
 
9149512.7%
 
411559.8%
 
111539.8%
 
1110639.0%
 
510318.7%
 
68747.4%
 
88186.9%
 
107206.1%
 
ValueCountFrequency (%) 
111539.8%
 
2152612.9%
 
33523.0%
 
411559.8%
 
510318.7%
 
ValueCountFrequency (%) 
1110639.0%
 
107206.1%
 
9149512.7%
 
88186.9%
 
7162613.8%
 

loudness
Real number (ℝ)

Distinct7121
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-8.215806654
Minimum-36.214
Maximum1.355
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:15.482079image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-36.214
5-th percentile-16.4424
Q1-9.994
median-7.314
Q3-5.341
95-th percentile-3.3652
Maximum1.355
Range37.569
Interquartile range (IQR)4.653

Descriptive statistics

Standard deviation4.239681578
Coefficient of variation (CV)-0.5160395999
Kurtosis4.265262994
Mean-8.215806654
Median Absolute Deviation (MAD)2.211
Skewness-1.660344543
Sum-97053.324
Variance17.97489988
MonotocityNot monotonic
2022-03-20T19:47:15.583092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-4.261100.1%
 
-5.497100.1%
 
-6.23790.1%
 
-5.57690.1%
 
-5.65990.1%
 
-3.43580.1%
 
-5.05980.1%
 
-4.67170.1%
 
-7.29470.1%
 
-8.27670.1%
 
Other values (7111)1172999.3%
 
ValueCountFrequency (%) 
-36.2141< 0.1%
 
-35.1541< 0.1%
 
-34.8251< 0.1%
 
-34.3781< 0.1%
 
-33.8381< 0.1%
 
ValueCountFrequency (%) 
1.3551< 0.1%
 
1.3422< 0.1%
 
0.8781< 0.1%
 
0.7321< 0.1%
 
0.1191< 0.1%
 

mode
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size92.3 KiB
1
7371 
0
4442 
ValueCountFrequency (%) 
1737162.4%
 
0444237.6%
 
2022-03-20T19:47:15.657095image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

speechiness
Real number (ℝ≥0)

Distinct1092
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07110714467
Minimum0.0225
Maximum0.935
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:15.724097image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0225
5-th percentile0.02776
Q10.0346
median0.0463
Q30.0765
95-th percentile0.2094
Maximum0.935
Range0.9125
Interquartile range (IQR)0.0419

Descriptive statistics

Standard deviation0.06778302817
Coefficient of variation (CV)0.9532520042
Kurtosis18.23077527
Mean0.07110714467
Median Absolute Deviation (MAD)0.0147
Skewness3.50512466
Sum839.9887
Variance0.004594538908
MonotocityNot monotonic
2022-03-20T19:47:15.824097image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.0317510.4%
 
0.0339510.4%
 
0.0392510.4%
 
0.0346500.4%
 
0.0315490.4%
 
0.0362480.4%
 
0.0335470.4%
 
0.0355440.4%
 
0.0316440.4%
 
0.0295430.4%
 
Other values (1082)1133596.0%
 
ValueCountFrequency (%) 
0.02252< 0.1%
 
0.02272< 0.1%
 
0.0232< 0.1%
 
0.02311< 0.1%
 
0.02323< 0.1%
 
ValueCountFrequency (%) 
0.9351< 0.1%
 
0.8911< 0.1%
 
0.8861< 0.1%
 
0.8621< 0.1%
 
0.6781< 0.1%
 

acousticness
Real number (ℝ≥0)

Distinct3578
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2399683165
Minimum0
Maximum0.996
Zeros3
Zeros (%)< 0.1%
Memory size92.3 KiB
2022-03-20T19:47:15.923432image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.72e-05
Q10.00189
median0.0561
Q30.421
95-th percentile0.9364
Maximum0.996
Range0.996
Interquartile range (IQR)0.41911

Descriptive statistics

Standard deviation0.3191422267
Coefficient of variation (CV)1.329934848
Kurtosis-0.120106577
Mean0.2399683165
Median Absolute Deviation (MAD)0.0560448
Skewness1.157504081
Sum2834.745723
Variance0.1018517608
MonotocityNot monotonic
2022-03-20T19:47:16.089214image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.136210.2%
 
0.989190.2%
 
0.994190.2%
 
0.102190.2%
 
0.135190.2%
 
0.992180.2%
 
0.128180.2%
 
0.0113170.1%
 
0.993170.1%
 
0.0133170.1%
 
Other values (3568)1162998.4%
 
ValueCountFrequency (%) 
03< 0.1%
 
1.02e-061< 0.1%
 
1.06e-062< 0.1%
 
1.11e-061< 0.1%
 
1.16e-061< 0.1%
 
ValueCountFrequency (%) 
0.99660.1%
 
0.99580.1%
 
0.994190.2%
 
0.993170.1%
 
0.992180.2%
 

instrumentalness
Real number (ℝ≥0)

Distinct4032
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1789914134
Minimum1e-06
Maximum0.996
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:16.209894image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1e-06
5-th percentile2.776e-06
Q19.61e-05
median0.00429
Q30.209
95-th percentile0.8864
Maximum0.996
Range0.995999
Interquartile range (IQR)0.2089039

Descriptive statistics

Standard deviation0.303809362
Coefficient of variation (CV)1.697340427
Kurtosis0.6793150111
Mean0.1789914134
Median Absolute Deviation (MAD)0.0042876
Skewness1.515475396
Sum2114.425566
Variance0.09230012843
MonotocityNot monotonic
2022-03-20T19:47:16.315386image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.000109190.2%
 
0.929180.2%
 
0.112160.1%
 
0.125160.1%
 
0.892160.1%
 
0.00124160.1%
 
0.827150.1%
 
0.897150.1%
 
0.0102140.1%
 
0.85140.1%
 
Other values (4022)1165498.7%
 
ValueCountFrequency (%) 
1e-062< 0.1%
 
1.01e-0660.1%
 
1.02e-0660.1%
 
1.03e-0680.1%
 
1.04e-064< 0.1%
 
ValueCountFrequency (%) 
0.9961< 0.1%
 
0.9871< 0.1%
 
0.9851< 0.1%
 
0.9831< 0.1%
 
0.9772< 0.1%
 

liveness
Real number (ℝ≥0)

Distinct1342
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1950959367
Minimum0.0119
Maximum0.992
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:16.430478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0119
5-th percentile0.06116
Q10.0969
median0.127
Q30.256
95-th percentile0.518
Maximum0.992
Range0.9801
Interquartile range (IQR)0.1591

Descriptive statistics

Standard deviation0.1597430621
Coefficient of variation (CV)0.8187923581
Kurtosis5.714627489
Mean0.1950959367
Median Absolute Deviation (MAD)0.046
Skewness2.196945289
Sum2304.6683
Variance0.02551784587
MonotocityNot monotonic
2022-03-20T19:47:16.655244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.111621.4%
 
0.1091351.1%
 
0.1041291.1%
 
0.1111291.1%
 
0.1081291.1%
 
0.1121241.0%
 
0.1071221.0%
 
0.1031161.0%
 
0.1011100.9%
 
0.1051010.9%
 
Other values (1332)1055689.4%
 
ValueCountFrequency (%) 
0.01191< 0.1%
 
0.01363< 0.1%
 
0.01441< 0.1%
 
0.01571< 0.1%
 
0.01691< 0.1%
 
ValueCountFrequency (%) 
0.9921< 0.1%
 
0.9891< 0.1%
 
0.9871< 0.1%
 
0.9863< 0.1%
 
0.9852< 0.1%
 

valence
Real number (ℝ≥0)

Distinct1263
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4701150258
Minimum0.0183
Maximum0.98
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:16.770445image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.0183
5-th percentile0.09192
Q10.271
median0.462
Q30.66
95-th percentile0.891
Maximum0.98
Range0.9617
Interquartile range (IQR)0.389

Descriptive statistics

Standard deviation0.244634556
Coefficient of variation (CV)0.5203717017
Kurtosis-0.9317933183
Mean0.4701150258
Median Absolute Deviation (MAD)0.194
Skewness0.1455450935
Sum5553.4688
Variance0.05984606598
MonotocityNot monotonic
2022-03-20T19:47:16.877409image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.512340.3%
 
0.399330.3%
 
0.389330.3%
 
0.486300.3%
 
0.352290.2%
 
0.547280.2%
 
0.322270.2%
 
0.254270.2%
 
0.566260.2%
 
0.397260.2%
 
Other values (1253)1152097.5%
 
ValueCountFrequency (%) 
0.01831< 0.1%
 
0.02151< 0.1%
 
0.02621< 0.1%
 
0.02641< 0.1%
 
0.02842< 0.1%
 
ValueCountFrequency (%) 
0.981< 0.1%
 
0.9791< 0.1%
 
0.9781< 0.1%
 
0.9775< 0.1%
 
0.9762< 0.1%
 

tempo
Real number (ℝ≥0)

Distinct9283
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.9286412
Minimum30.557
Maximum217.416
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:16.994448image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum30.557
5-th percentile79.9952
Q1100.001
median120.046
Q3141.877
95-th percentile175.883
Maximum217.416
Range186.859
Interquartile range (IQR)41.876

Descriptive statistics

Standard deviation29.43088326
Coefficient of variation (CV)0.2394143705
Kurtosis-0.4094982723
Mean122.9286412
Median Absolute Deviation (MAD)20.143
Skewness0.4002905127
Sum1452156.039
Variance866.1768894
MonotocityNot monotonic
2022-03-20T19:47:17.104391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
120.02480.1%
 
12080.1%
 
120.00670.1%
 
99.98370.1%
 
128.0460.1%
 
111.67660.1%
 
132.52660.1%
 
119.98960.1%
 
126.01460.1%
 
119.99560.1%
 
Other values (9273)1174799.4%
 
ValueCountFrequency (%) 
30.5571< 0.1%
 
34.1321< 0.1%
 
42.9561< 0.1%
 
48.7181< 0.1%
 
49.321< 0.1%
 
ValueCountFrequency (%) 
217.4162< 0.1%
 
216.0911< 0.1%
 
216.0532< 0.1%
 
216.021< 0.1%
 
214.3961< 0.1%
 

duration_in min/ms
Real number (ℝ≥0)

Distinct9545
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212944.5899
Minimum0.50165
Maximum1477187
Zeros0
Zeros (%)0.0%
Memory size92.3 KiB
2022-03-20T19:47:17.217617image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.50165
5-th percentile3.52478
Q1175533
median217883
Q3263587
95-th percentile378264.4
Maximum1477187
Range1477186.498
Interquartile range (IQR)88054

Descriptive statistics

Standard deviation115856.1114
Coefficient of variation (CV)0.5440669397
Kurtosis9.564381542
Mean212944.5899
Median Absolute Deviation (MAD)43736
Skewness1.027183217
Sum2515514441
Variance1.342263854e+10
MonotocityNot monotonic
2022-03-20T19:47:17.318686image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
235000120.1%
 
23000080.1%
 
25220060.1%
 
21900060.1%
 
24000060.1%
 
22000060.1%
 
20800060.1%
 
19200060.1%
 
20400060.1%
 
25300060.1%
 
Other values (9535)1174599.4%
 
ValueCountFrequency (%) 
0.501651< 0.1%
 
0.969151< 0.1%
 
0.9871166671< 0.1%
 
0.9919833331< 0.1%
 
1.0274833331< 0.1%
 
ValueCountFrequency (%) 
14771871< 0.1%
 
14124511< 0.1%
 
13859072< 0.1%
 
12845071< 0.1%
 
12446131< 0.1%
 

time_signature
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size92.3 KiB
4
10717 
3
 
879
5
 
128
1
 
89
ValueCountFrequency (%) 
41071790.7%
 
38797.4%
 
51281.1%
 
1890.8%
 
2022-03-20T19:47:17.412283image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2022-03-20T19:47:17.464749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-03-20T19:47:17.518417image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Class
Real number (ℝ≥0)

ZEROS

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.622619148
Minimum0
Maximum10
Zeros386
Zeros (%)3.3%
Memory size92.3 KiB
2022-03-20T19:47:17.588872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median8
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.246655996
Coefficient of variation (CV)0.490237461
Kurtosis-0.9024442196
Mean6.622619148
Median Absolute Deviation (MAD)2
Skewness-0.6441247977
Sum78233
Variance10.54077516
MonotocityIncreasing
2022-03-20T19:47:17.662179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
10337428.6%
 
6203917.3%
 
8152312.9%
 
910999.3%
 
110378.8%
 
29568.1%
 
55174.4%
 
74643.9%
 
03863.3%
 
32702.3%
 
ValueCountFrequency (%) 
03863.3%
 
110378.8%
 
29568.1%
 
32702.3%
 
41481.3%
 
ValueCountFrequency (%) 
10337428.6%
 
910999.3%
 
8152312.9%
 
74643.9%
 
6203917.3%
 

Interactions

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2022-03-20T19:47:14.162023image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-03-20T19:47:17.745179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-03-20T19:47:17.896179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-03-20T19:47:18.429030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-03-20T19:47:18.578030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-03-20T19:47:14.312024image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-03-20T19:47:14.523533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Sample

First rows

Popularitydanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/mstime_signatureClass
0400.5650.2928-13.12410.02550.88900.0012600.11200.217078.5353.50363310
110.5580.4391-9.67610.02740.24800.0016500.10200.0381103.9584.94711710
2210.4720.5342-10.74200.03420.76000.0861000.08930.3830184.0144.97283310
3350.5940.6191-11.12300.04780.59700.0001440.06940.385089.6915.83578310
4210.7320.5502-8.71100.03970.80900.0910000.09140.2350132.9746.13378310
5250.5350.4987-8.76810.03460.01840.0072300.19100.3340150.0318.51725010
6460.6730.3577-7.08710.02880.43400.0000140.31300.5470107.9842.72236730
7370.6870.2978-10.02910.02560.52700.2030000.13700.600077.0963.03353330
8300.2580.32110-11.62900.03070.61200.2130000.45300.064170.0153.15510030
9520.5870.2992-6.64910.03270.85300.0000020.14900.184096.6573.16778330

Last rows

Popularitydanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/mstime_signatureClass
11803530.1910.8299-3.38100.04470.0000270.0000210.36200.1910116.007276667.0510
11804330.5090.9619-4.84510.07130.0897000.7690000.25300.7530110.100276826.0510
11805270.5310.6864-6.32100.10900.0669000.1340000.09990.5090109.096337007.0510
11806260.6600.7267-7.20110.05080.0076600.8680000.27000.2750123.468340933.0510
11807340.2490.9864-7.65610.11500.0613000.4730000.03650.0792108.575342800.0510
11808420.3700.4763-12.73000.05350.1010000.0025200.07790.2940119.337344400.0510
11809300.3880.9688-4.73610.06860.0009930.0014500.91300.4120128.907387874.0510
11810290.3930.6239-13.09110.04760.1280000.0010600.09190.2860165.069408000.0510
11811210.3050.5012-10.17900.03370.0984000.4190000.13800.349090.574422213.0510
11812230.5210.1939-17.46700.06640.9480000.0337000.15200.2360138.780485227.0510

Duplicate rows

Most frequent

Popularitydanceabilityenergykeyloudnessmodespeechinessacousticnessinstrumentalnesslivenessvalencetempoduration_in min/mstime_signatureClasscount
010.5620.9614-7.33810.06170.0048600.7960000.14900.960125.036450547.0412
1210.4030.5795-8.12300.03880.1280000.0219000.09600.236100.019209400.0492
2360.4750.15710-19.06310.05670.9760000.0348000.07760.519169.224183066.0422
3400.1490.9089-7.94100.08620.0000170.8870000.07130.147143.237471280.0382
4430.3100.6104-9.41500.07230.1470000.0004760.17900.14488.1321385907.04102
5440.4290.8735-6.12110.05390.0036200.2990000.11100.43979.529305345.04102
6450.2220.5975-10.92410.05600.2650000.1550000.41100.25180.6541121253.03102
7460.3830.5112-7.14300.03690.1680000.0061000.25600.294121.049469445.0422
8470.5510.9181-5.20510.06420.0150000.0006220.09300.600170.399231720.0482
9480.8230.5697-9.30100.04980.0571000.0024200.09380.831111.974258316.0412